code: def train(model, sentence):
      trainer = dy.SimpleSGDTrainer(model)
      for i in range(600):
          loss = get_loss(
              sentence, sentence, enc_fwd_lstm, enc_bwd_lstm, dec_lstm
          )
          loss_value = loss.value()
          loss.backward()
          trainer.update()
          if i % 20 == 0:
              print(loss_value)
              print(
                  generate(
                      sentence, enc_fwd_lstm, enc_bwd_lstm, dec_lstm
                  )
              )
  
file_path: dynet/examples/sequence-to-sequence/attention.py
imports: import dynet
  import random
label_desc: Use image node_id 8 for calling a global function with example usage: train(model, sentence) without return types